Empirical curvelet transform based deep DenseNet model to predict NDVI using RGB drone imagery data-Reference-Cited by-同舟云学术

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Empirical curvelet transform based deep DenseNet model to predict NDVI using RGB drone imagery data

Published:2024-06 Issue: Volume:221 Page:108964
ISSN:0168-1699
Container-title:Computers and Electronics in Agriculture
language:en
Short-container-title:Computers and Electronics in Agriculture

Author:

Diykh Mohammed,Ali Mumtaz,Jamei Mehdi,Abdulla Shahab,Uddin Md Palash,Farooque Aitazaz Ahsan,Labban Abdulhaleem H.,Alabdally Hussein

Funder

Natural Sciences and Engineering Research Council of Canada

Atlantic Canada Opportunities Agency

University of Prince Edward Island

Publisher

Elsevier BV

Reference36 articles.

1. Abai, Z. and N. Rajmalwar (2019). “Densenet models for tiny imagenet classification.” arXiv preprint arXiv:1904.10429.

2. Generative adversarial network: an overview of theory and applications;Aggarwal;International Journal of Information Management Data Insights,2021

3. An improved DenseNet model for prediction of stock market using stock technical indicators;Albahli;Expert Syst. Appl.,2023

4. Optimising realism of synthetic images using cycle generative adversarial networks for improved part segmentation;Barth;Comput. Electron. Agric.,2020

5. Deep spatial-temporal graph modeling for efficient NDVI forecasting;Beyer;Smart Agricultural Technology,2023

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